Instructions to use BlueSR/HerbaScan_Weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use BlueSR/HerbaScan_Weights with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf BlueSR/HerbaScan_Weights:Q4_K_M # Run inference directly in the terminal: llama cli -hf BlueSR/HerbaScan_Weights:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf BlueSR/HerbaScan_Weights:Q4_K_M # Run inference directly in the terminal: llama cli -hf BlueSR/HerbaScan_Weights:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf BlueSR/HerbaScan_Weights:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf BlueSR/HerbaScan_Weights:Q4_K_M
Use Docker
docker model run hf.co/BlueSR/HerbaScan_Weights:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use BlueSR/HerbaScan_Weights with Ollama:
ollama run hf.co/BlueSR/HerbaScan_Weights:Q4_K_M
- Unsloth Desktop
- Pi
How to use BlueSR/HerbaScan_Weights with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BlueSR/HerbaScan_Weights:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "BlueSR/HerbaScan_Weights:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use BlueSR/HerbaScan_Weights with Docker Model Runner:
docker model run hf.co/BlueSR/HerbaScan_Weights:Q4_K_M
- Lemonade
How to use BlueSR/HerbaScan_Weights with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull BlueSR/HerbaScan_Weights:Q4_K_M
Run and chat with the model
lemonade run user.HerbaScan_Weights-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use BlueSR/HerbaScan_Weights with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BlueSR/HerbaScan_Weights:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default BlueSR/HerbaScan_Weights:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use BlueSR/HerbaScan_Weights with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BlueSR/HerbaScan_Weights:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "BlueSR/HerbaScan_Weights:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
metadata extraction glm, lora adapters and ollama qwen gguf that requires setup
#7
by MicWJJ - opened
- .gitattributes +1 -0
- metadata_extraction/models/glm-ocr-adapter/adapter_config.json +45 -0
- metadata_extraction/models/glm-ocr-adapter/adapter_model.safetensors +3 -0
- metadata_extraction/models/glm-ocr/chat_template.jinja +140 -0
- metadata_extraction/models/glm-ocr/config.json +70 -0
- metadata_extraction/models/glm-ocr/generation_config.json +10 -0
- metadata_extraction/models/glm-ocr/model.safetensors +3 -0
- metadata_extraction/models/glm-ocr/processor_config.json +63 -0
- metadata_extraction/models/glm-ocr/tokenizer.json +0 -0
- metadata_extraction/models/glm-ocr/tokenizer_config.json +50 -0
- metadata_extraction/ollama/qwen2.5-7b-instruct/LICENSE +202 -0
- metadata_extraction/ollama/qwen2.5-7b-instruct/Modelfile +54 -0
- metadata_extraction/ollama/qwen2.5-7b-instruct/qwen2.5-7b-instruct-q4_k_m.gguf +3 -0
- metadata_extraction/weights/best_text_detection.pt +3 -0
.gitattributes
CHANGED
|
@@ -657,3 +657,4 @@ measurement_pipeline/herbarium_rulers/ruler_crops_normalized/L__0007231_Dillen_r
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| 657 |
measurement_pipeline/plantsam/BBS2_1024_2_epoch5.torch filter=lfs diff=lfs merge=lfs -text
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| 658 |
models/qwen-vl-2b/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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| 659 |
models/qwen-vl/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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| 657 |
measurement_pipeline/plantsam/BBS2_1024_2_epoch5.torch filter=lfs diff=lfs merge=lfs -text
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| 658 |
models/qwen-vl-2b/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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| 659 |
models/qwen-vl/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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| 660 |
+
metadata_extraction/ollama/qwen2.5-7b-instruct/qwen2.5-7b-instruct-q4_k_m.gguf filter=lfs diff=lfs merge=lfs -text
|
metadata_extraction/models/glm-ocr-adapter/adapter_config.json
ADDED
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@@ -0,0 +1,45 @@
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+
{
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| 2 |
+
"alora_invocation_tokens": null,
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| 3 |
+
"alpha_pattern": {},
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| 4 |
+
"arrow_config": null,
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| 5 |
+
"auto_mapping": {
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| 6 |
+
"base_model_class": "GlmOcrForConditionalGeneration",
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| 7 |
+
"parent_library": "transformers.models.glm_ocr.modeling_glm_ocr"
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| 8 |
+
},
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| 9 |
+
"base_model_name_or_path": "C:\\xampp\\htdocs\\COS40005_Computing_Technology_Project_A\\digitisation_pipeline\\models\\glm-ocr",
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| 10 |
+
"bias": "none",
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| 11 |
+
"corda_config": null,
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| 12 |
+
"ensure_weight_tying": false,
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| 13 |
+
"eva_config": null,
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| 14 |
+
"exclude_modules": null,
|
| 15 |
+
"fan_in_fan_out": false,
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| 16 |
+
"inference_mode": true,
|
| 17 |
+
"init_lora_weights": true,
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| 18 |
+
"layer_replication": null,
|
| 19 |
+
"layers_pattern": null,
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| 20 |
+
"layers_to_transform": null,
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| 21 |
+
"loftq_config": {},
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| 22 |
+
"lora_alpha": 32,
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| 23 |
+
"lora_bias": false,
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| 24 |
+
"lora_dropout": 0.05,
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| 25 |
+
"lora_ga_config": null,
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| 26 |
+
"megatron_config": null,
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| 27 |
+
"megatron_core": "megatron.core",
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| 28 |
+
"modules_to_save": null,
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| 29 |
+
"monteclora_config": null,
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| 30 |
+
"peft_type": "LORA",
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| 31 |
+
"peft_version": "0.20.0",
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| 32 |
+
"qalora_group_size": 16,
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| 33 |
+
"r": 16,
|
| 34 |
+
"rank_pattern": {},
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| 35 |
+
"revision": null,
|
| 36 |
+
"target_modules": "(model\\.language_model\\.layers\\.\\d+\\.(self_attn\\.(q_proj|k_proj|v_proj|o_proj)|mlp\\.(gate_up_proj|down_proj)))|(model\\.visual\\.blocks\\.\\d+\\.(attn\\.(qkv|proj)|mlp\\.(gate_proj|up_proj|down_proj)))",
|
| 37 |
+
"target_parameters": null,
|
| 38 |
+
"task_type": null,
|
| 39 |
+
"trainable_token_indices": null,
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| 40 |
+
"use_bdlora": null,
|
| 41 |
+
"use_dora": false,
|
| 42 |
+
"use_qalora": false,
|
| 43 |
+
"use_rslora": false,
|
| 44 |
+
"velora_config": null
|
| 45 |
+
}
|
metadata_extraction/models/glm-ocr-adapter/adapter_model.safetensors
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:991d8784018d20cf2af1366ab424904f76de60b4566b8260273957d90622e5b0
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| 3 |
+
size 62975784
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metadata_extraction/models/glm-ocr/chat_template.jinja
ADDED
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@@ -0,0 +1,140 @@
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| 1 |
+
[gMASK]<sop>
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| 2 |
+
{%- if tools -%}
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| 3 |
+
<|system|>
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| 4 |
+
# Tools
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| 5 |
+
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| 6 |
+
You may call one or more functions to assist with the user query.
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| 7 |
+
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| 8 |
+
You are provided with function signatures within <tools></tools> XML tags:
|
| 9 |
+
<tools>
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| 10 |
+
{% for tool in tools %}
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| 11 |
+
{{ tool | tojson(ensure_ascii=False) }}
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| 12 |
+
{% endfor %}
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| 13 |
+
</tools>
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| 14 |
+
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| 15 |
+
For each function call, output the function name and arguments within the following XML format:
|
| 16 |
+
<tool_call>{function-name}
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| 17 |
+
<arg_key>{arg-key-1}</arg_key>
|
| 18 |
+
<arg_value>{arg-value-1}</arg_value>
|
| 19 |
+
<arg_key>{arg-key-2}</arg_key>
|
| 20 |
+
<arg_value>{arg-value-2}</arg_value>
|
| 21 |
+
...
|
| 22 |
+
</tool_call>{%- endif -%}
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| 23 |
+
{%- macro visible_text(content) -%}
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| 24 |
+
{%- if content is string -%}
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| 25 |
+
{{- content }}
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| 26 |
+
{%- elif content is iterable and content is not mapping -%}
|
| 27 |
+
{%- for item in content -%}
|
| 28 |
+
{%- if item is mapping and item.type == 'text' -%}
|
| 29 |
+
{{- item.text }}
|
| 30 |
+
{%- elif item is mapping and (item.type == 'image' or 'image' in item) -%}
|
| 31 |
+
<|begin_of_image|><|image|><|end_of_image|>
|
| 32 |
+
{%- elif item is mapping and (item.type == 'video' or 'video' in item) -%}
|
| 33 |
+
<|begin_of_video|><|video|><|end_of_video|>
|
| 34 |
+
{%- elif item is string -%}
|
| 35 |
+
{{- item }}
|
| 36 |
+
{%- endif -%}
|
| 37 |
+
{%- endfor -%}
|
| 38 |
+
{%- else -%}
|
| 39 |
+
{{- content }}
|
| 40 |
+
{%- endif -%}
|
| 41 |
+
{%- endmacro -%}
|
| 42 |
+
{%- set ns = namespace(last_user_index=-1) %}
|
| 43 |
+
{%- for m in messages %}
|
| 44 |
+
{%- if m.role == 'user' %}
|
| 45 |
+
{% set ns.last_user_index = loop.index0 -%}
|
| 46 |
+
{%- endif %}
|
| 47 |
+
{%- endfor %}
|
| 48 |
+
{% for m in messages %}
|
| 49 |
+
{%- if m.role == 'user' -%}<|user|>
|
| 50 |
+
{% if m.content is string %}
|
| 51 |
+
{{ m.content }}
|
| 52 |
+
{%- else %}
|
| 53 |
+
{%- for item in m.content %}
|
| 54 |
+
{% if item.type == 'video' or 'video' in item %}
|
| 55 |
+
<|begin_of_video|><|video|><|end_of_video|>{% elif item.type == 'image' or 'image' in item %}
|
| 56 |
+
<|begin_of_image|><|image|><|end_of_image|>{% elif item.type == 'text' %}
|
| 57 |
+
{{ item.text }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endfor %}
|
| 60 |
+
{%- endif %}
|
| 61 |
+
{{- '/nothink' if (enable_thinking is defined and not enable_thinking and not visible_text(m.content).endswith("/nothink")) else '' -}}
|
| 62 |
+
{%- elif m.role == 'assistant' -%}
|
| 63 |
+
<|assistant|>
|
| 64 |
+
{%- set reasoning_content = '' %}
|
| 65 |
+
{%- set content = visible_text(m.content) %}
|
| 66 |
+
{%- if m.reasoning_content is string %}
|
| 67 |
+
{%- set reasoning_content = m.reasoning_content %}
|
| 68 |
+
{%- else %}
|
| 69 |
+
{%- if '</think>' in content %}
|
| 70 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 71 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 72 |
+
{%- endif %}
|
| 73 |
+
{%- endif %}
|
| 74 |
+
{%- if loop.index0 > ns.last_user_index and reasoning_content -%}
|
| 75 |
+
{{ '\n<think>' + reasoning_content.strip() + '</think>'}}
|
| 76 |
+
{%- else -%}
|
| 77 |
+
{{ '\n<think></think>' }}
|
| 78 |
+
{%- endif -%}
|
| 79 |
+
{%- if content.strip() -%}
|
| 80 |
+
{{ '\n' + content.strip() }}
|
| 81 |
+
{%- endif -%}
|
| 82 |
+
{% if m.tool_calls %}
|
| 83 |
+
{% for tc in m.tool_calls %}
|
| 84 |
+
{%- if tc.function %}
|
| 85 |
+
{%- set tc = tc.function %}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{{ '\n<tool_call>' + tc.name }}
|
| 88 |
+
{% set _args = tc.arguments %}
|
| 89 |
+
{% for k, v in _args.items() %}
|
| 90 |
+
<arg_key>{{ k }}</arg_key>
|
| 91 |
+
<arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>
|
| 92 |
+
{% endfor %}
|
| 93 |
+
</tool_call>{% endfor %}
|
| 94 |
+
{% endif %}
|
| 95 |
+
{%- elif m.role == 'tool' -%}
|
| 96 |
+
{%- if m.content is string -%}
|
| 97 |
+
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
| 98 |
+
{{- '<|observation|>' }}
|
| 99 |
+
{%- endif %}
|
| 100 |
+
{{- '\n<tool_response>\n' }}
|
| 101 |
+
{{- m.content }}
|
| 102 |
+
{{- '\n</tool_response>' }}
|
| 103 |
+
{% elif m.content is iterable and m.content is not mapping %}
|
| 104 |
+
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
| 105 |
+
{{- '<|observation|>' }}
|
| 106 |
+
{%- endif %}
|
| 107 |
+
{{- '\n<tool_response>\n' }}
|
| 108 |
+
{%- for tr in m.content -%}
|
| 109 |
+
{%- if tr is mapping and tr.type is defined -%}
|
| 110 |
+
{%- set t = tr.type | lower -%}
|
| 111 |
+
{%- if t == 'text' and tr.text is defined -%}
|
| 112 |
+
{{ tr.text }}
|
| 113 |
+
{%- elif t in ['image', 'image_url'] -%}
|
| 114 |
+
<|begin_of_image|><|image|><|end_of_image|>
|
| 115 |
+
{%- elif t in ['video', 'video_url'] -%}
|
| 116 |
+
<|begin_of_video|><|video|><|end_of_video|>
|
| 117 |
+
{%- else -%}
|
| 118 |
+
{{ tr | tojson(ensure_ascii=False) }}
|
| 119 |
+
{%- endif -%}
|
| 120 |
+
{%- else -%}
|
| 121 |
+
{{ tr.output if tr.output is defined else tr }}
|
| 122 |
+
{%- endif -%}
|
| 123 |
+
{%- endfor -%}
|
| 124 |
+
{{- '\n</tool_response>' }}
|
| 125 |
+
{%- else -%}
|
| 126 |
+
<|observation|>{% for tr in m.content %}
|
| 127 |
+
|
| 128 |
+
<tool_response>
|
| 129 |
+
{{ tr.output if tr.output is defined else tr }}
|
| 130 |
+
</tool_response>{% endfor -%}
|
| 131 |
+
{% endif -%}
|
| 132 |
+
{%- elif m.role == 'system' -%}
|
| 133 |
+
<|system|>
|
| 134 |
+
{{ visible_text(m.content) }}
|
| 135 |
+
{%- endif -%}
|
| 136 |
+
{%- endfor -%}
|
| 137 |
+
{%- if add_generation_prompt -%}
|
| 138 |
+
<|assistant|>
|
| 139 |
+
{{'<think></think>\n' if (enable_thinking is defined and not enable_thinking) else ''}}
|
| 140 |
+
{%- endif -%}
|
metadata_extraction/models/glm-ocr/config.json
ADDED
|
@@ -0,0 +1,70 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"GlmOcrForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
+
"dtype": "bfloat16",
|
| 6 |
+
"image_end_token_id": 59257,
|
| 7 |
+
"image_start_token_id": 59256,
|
| 8 |
+
"image_token_id": 59280,
|
| 9 |
+
"model_type": "glm_ocr",
|
| 10 |
+
"text_config": {
|
| 11 |
+
"attention_bias": false,
|
| 12 |
+
"attention_dropout": 0.0,
|
| 13 |
+
"dtype": "bfloat16",
|
| 14 |
+
"eos_token_id": [
|
| 15 |
+
59246,
|
| 16 |
+
59253
|
| 17 |
+
],
|
| 18 |
+
"head_dim": 128,
|
| 19 |
+
"hidden_act": "silu",
|
| 20 |
+
"hidden_size": 1536,
|
| 21 |
+
"initializer_range": 0.02,
|
| 22 |
+
"intermediate_size": 4608,
|
| 23 |
+
"max_position_embeddings": 131072,
|
| 24 |
+
"model_type": "glm_ocr_text",
|
| 25 |
+
"num_attention_heads": 16,
|
| 26 |
+
"num_hidden_layers": 16,
|
| 27 |
+
"num_key_value_heads": 8,
|
| 28 |
+
"num_nextn_predict_layers": 1,
|
| 29 |
+
"pad_token_id": 59246,
|
| 30 |
+
"rms_norm_eps": 1e-05,
|
| 31 |
+
"rope_parameters": {
|
| 32 |
+
"mrope_section": [
|
| 33 |
+
16,
|
| 34 |
+
24,
|
| 35 |
+
24
|
| 36 |
+
],
|
| 37 |
+
"partial_rotary_factor": 1.0,
|
| 38 |
+
"rope_theta": 10000,
|
| 39 |
+
"rope_type": "default"
|
| 40 |
+
},
|
| 41 |
+
"tie_word_embeddings": false,
|
| 42 |
+
"use_cache": true,
|
| 43 |
+
"vocab_size": 59392
|
| 44 |
+
},
|
| 45 |
+
"tie_word_embeddings": false,
|
| 46 |
+
"transformers_version": "5.8.0.dev0",
|
| 47 |
+
"video_end_token_id": 59259,
|
| 48 |
+
"video_start_token_id": 59258,
|
| 49 |
+
"video_token_id": 59281,
|
| 50 |
+
"vision_config": {
|
| 51 |
+
"attention_bias": true,
|
| 52 |
+
"attention_dropout": 0.0,
|
| 53 |
+
"depth": 24,
|
| 54 |
+
"dtype": "bfloat16",
|
| 55 |
+
"hidden_act": "silu",
|
| 56 |
+
"hidden_dropout_prob": 0.0,
|
| 57 |
+
"hidden_size": 1024,
|
| 58 |
+
"image_size": 336,
|
| 59 |
+
"in_channels": 3,
|
| 60 |
+
"initializer_range": 0.02,
|
| 61 |
+
"intermediate_size": 4096,
|
| 62 |
+
"model_type": "glm_ocr_vision",
|
| 63 |
+
"num_heads": 16,
|
| 64 |
+
"out_hidden_size": 1536,
|
| 65 |
+
"patch_size": 14,
|
| 66 |
+
"rms_norm_eps": 1e-05,
|
| 67 |
+
"spatial_merge_size": 2,
|
| 68 |
+
"temporal_patch_size": 2
|
| 69 |
+
}
|
| 70 |
+
}
|
metadata_extraction/models/glm-ocr/generation_config.json
ADDED
|
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"do_sample": false,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
59246,
|
| 6 |
+
59253
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 59246,
|
| 9 |
+
"transformers_version": "5.8.0.dev0"
|
| 10 |
+
}
|
metadata_extraction/models/glm-ocr/model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7deb53e3f51baa7f61b73536cefe70f3075acdf4f58506e18e59490943d0942b
|
| 3 |
+
size 2214872552
|
metadata_extraction/models/glm-ocr/processor_config.json
ADDED
|
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"image_processor": {
|
| 3 |
+
"do_convert_rgb": true,
|
| 4 |
+
"do_normalize": true,
|
| 5 |
+
"do_rescale": true,
|
| 6 |
+
"do_resize": true,
|
| 7 |
+
"image_mean": [
|
| 8 |
+
0.48145466,
|
| 9 |
+
0.4578275,
|
| 10 |
+
0.40821073
|
| 11 |
+
],
|
| 12 |
+
"image_processor_type": "Glm46VImageProcessor",
|
| 13 |
+
"image_std": [
|
| 14 |
+
0.26862954,
|
| 15 |
+
0.26130258,
|
| 16 |
+
0.27577711
|
| 17 |
+
],
|
| 18 |
+
"merge_size": 2,
|
| 19 |
+
"patch_size": 14,
|
| 20 |
+
"resample": 3,
|
| 21 |
+
"rescale_factor": 0.00392156862745098,
|
| 22 |
+
"size": {
|
| 23 |
+
"longest_edge": 9633792,
|
| 24 |
+
"shortest_edge": 12544
|
| 25 |
+
},
|
| 26 |
+
"temporal_patch_size": 2
|
| 27 |
+
},
|
| 28 |
+
"processor_class": "Glm46VProcessor",
|
| 29 |
+
"video_processor": {
|
| 30 |
+
"do_convert_rgb": true,
|
| 31 |
+
"do_normalize": true,
|
| 32 |
+
"do_rescale": true,
|
| 33 |
+
"do_resize": true,
|
| 34 |
+
"do_sample_frames": true,
|
| 35 |
+
"fps": 2,
|
| 36 |
+
"image_mean": [
|
| 37 |
+
0.48145466,
|
| 38 |
+
0.4578275,
|
| 39 |
+
0.40821073
|
| 40 |
+
],
|
| 41 |
+
"image_std": [
|
| 42 |
+
0.26862954,
|
| 43 |
+
0.26130258,
|
| 44 |
+
0.27577711
|
| 45 |
+
],
|
| 46 |
+
"max_duration": 300,
|
| 47 |
+
"max_image_size": {
|
| 48 |
+
"longest_edge": 47040000
|
| 49 |
+
},
|
| 50 |
+
"merge_size": 2,
|
| 51 |
+
"num_frames": 16,
|
| 52 |
+
"patch_size": 14,
|
| 53 |
+
"resample": 3,
|
| 54 |
+
"rescale_factor": 0.00392156862745098,
|
| 55 |
+
"return_metadata": false,
|
| 56 |
+
"size": {
|
| 57 |
+
"longest_edge": 9633792,
|
| 58 |
+
"shortest_edge": 12544
|
| 59 |
+
},
|
| 60 |
+
"temporal_patch_size": 2,
|
| 61 |
+
"video_processor_type": "Glm46VVideoProcessor"
|
| 62 |
+
}
|
| 63 |
+
}
|
metadata_extraction/models/glm-ocr/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
metadata_extraction/models/glm-ocr/tokenizer_config.json
ADDED
|
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"backend": "tokenizers",
|
| 3 |
+
"clean_up_tokenization_spaces": false,
|
| 4 |
+
"eos_token": "<|endoftext|>",
|
| 5 |
+
"extra_special_tokens": [
|
| 6 |
+
"<|endoftext|>",
|
| 7 |
+
"[MASK]",
|
| 8 |
+
"[gMASK]",
|
| 9 |
+
"[sMASK]",
|
| 10 |
+
"<sop>",
|
| 11 |
+
"<eop>",
|
| 12 |
+
"<|system|>",
|
| 13 |
+
"<|user|>",
|
| 14 |
+
"<|assistant|>",
|
| 15 |
+
"<|observation|>",
|
| 16 |
+
"<|begin_of_image|>",
|
| 17 |
+
"<|end_of_image|>",
|
| 18 |
+
"<|begin_of_video|>",
|
| 19 |
+
"<|end_of_video|>",
|
| 20 |
+
"<|begin_of_audio|>",
|
| 21 |
+
"<|end_of_audio|>",
|
| 22 |
+
"<|begin_of_transcription|>",
|
| 23 |
+
"<|end_of_transcription|>",
|
| 24 |
+
"<|code_prefix|>",
|
| 25 |
+
"<|code_middle|>",
|
| 26 |
+
"<|code_suffix|>",
|
| 27 |
+
"<think>",
|
| 28 |
+
"</think>",
|
| 29 |
+
"<tool_call>",
|
| 30 |
+
"</tool_call>",
|
| 31 |
+
"<tool_response>",
|
| 32 |
+
"</tool_response>",
|
| 33 |
+
"<arg_key>",
|
| 34 |
+
"</arg_key>",
|
| 35 |
+
"<arg_value>",
|
| 36 |
+
"</arg_value>",
|
| 37 |
+
"/nothink",
|
| 38 |
+
"<|begin_of_box|>",
|
| 39 |
+
"<|end_of_box|>",
|
| 40 |
+
"<|image|>",
|
| 41 |
+
"<|video|>"
|
| 42 |
+
],
|
| 43 |
+
"is_local": false,
|
| 44 |
+
"local_files_only": false,
|
| 45 |
+
"model_max_length": 655380,
|
| 46 |
+
"pad_token": "<|endoftext|>",
|
| 47 |
+
"padding_side": "left",
|
| 48 |
+
"processor_class": "Glm46VProcessor",
|
| 49 |
+
"tokenizer_class": "TokenizersBackend"
|
| 50 |
+
}
|
metadata_extraction/ollama/qwen2.5-7b-instruct/LICENSE
ADDED
|
@@ -0,0 +1,202 @@
|
|
|
|
|
|
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|
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|
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|
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|
|
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|
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|
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|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
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|
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Apache License
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http://www.apache.org/licenses/
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TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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APPENDIX: How to apply the Apache License to your work.
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metadata_extraction/ollama/qwen2.5-7b-instruct/Modelfile
ADDED
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FROM ./qwen2.5-7b-instruct-q4_k_m.gguf
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+
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+
SYSTEM You are Qwen, created by Alibaba Cloud. You are a helpful assistant.
|
| 4 |
+
|
| 5 |
+
TEMPLATE """{{- if .Messages }}
|
| 6 |
+
{{- if or .System .Tools }}<|im_start|>system
|
| 7 |
+
{{- if .System }}
|
| 8 |
+
{{ .System }}
|
| 9 |
+
{{- end }}
|
| 10 |
+
{{- if .Tools }}
|
| 11 |
+
|
| 12 |
+
# Tools
|
| 13 |
+
|
| 14 |
+
You may call one or more functions to assist with the user query.
|
| 15 |
+
|
| 16 |
+
You are provided with function signatures within <tools></tools> XML tags:
|
| 17 |
+
<tools>
|
| 18 |
+
{{- range .Tools }}
|
| 19 |
+
{"type": "function", "function": {{ .Function }}}
|
| 20 |
+
{{- end }}
|
| 21 |
+
</tools>
|
| 22 |
+
|
| 23 |
+
For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
|
| 24 |
+
<tool_call>
|
| 25 |
+
{"name": <function-name>, "arguments": <args-json-object>}
|
| 26 |
+
</tool_call>
|
| 27 |
+
{{- end }}<|im_end|>
|
| 28 |
+
{{ end }}
|
| 29 |
+
{{- range $i, $_ := .Messages }}
|
| 30 |
+
{{- $last := eq (len (slice $.Messages $i)) 1 -}}
|
| 31 |
+
{{- if eq .Role "user" }}<|im_start|>user
|
| 32 |
+
{{ .Content }}<|im_end|>
|
| 33 |
+
{{ else if eq .Role "assistant" }}<|im_start|>assistant
|
| 34 |
+
{{ if .Content }}{{ .Content }}
|
| 35 |
+
{{- else if .ToolCalls }}<tool_call>
|
| 36 |
+
{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
|
| 37 |
+
{{ end }}</tool_call>
|
| 38 |
+
{{- end }}{{ if not $last }}<|im_end|>
|
| 39 |
+
{{ end }}
|
| 40 |
+
{{- else if eq .Role "tool" }}<|im_start|>user
|
| 41 |
+
<tool_response>
|
| 42 |
+
{{ .Content }}
|
| 43 |
+
</tool_response><|im_end|>
|
| 44 |
+
{{ end }}
|
| 45 |
+
{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant
|
| 46 |
+
{{ end }}
|
| 47 |
+
{{- end }}
|
| 48 |
+
{{- else }}
|
| 49 |
+
{{- if .System }}<|im_start|>system
|
| 50 |
+
{{ .System }}<|im_end|>
|
| 51 |
+
{{ end }}{{ if .Prompt }}<|im_start|>user
|
| 52 |
+
{{ .Prompt }}<|im_end|>
|
| 53 |
+
{{ end }}<|im_start|>assistant
|
| 54 |
+
{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}"""
|
metadata_extraction/ollama/qwen2.5-7b-instruct/qwen2.5-7b-instruct-q4_k_m.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
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|
| 1 |
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2bada8a7450677000f678be90653b85d364de7db25eb5ea54136ada5f3933730
|
| 3 |
+
size 4683073952
|
metadata_extraction/weights/best_text_detection.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0246d7508ab635959b1dcf1ee082274bf40b3e3358876d4114326a968732ff1b
|
| 3 |
+
size 22553002
|